Blood pump control system and method for controlling a blood pump

ABSTRACT

Methods are provided for controlling the speed of a pump based on a valve state index and/or for deriving a valve state from time-series signal representing a pressure difference or a flow rate. The methods may be employed in blood pump systems or in blood pump control systems.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a 371 nationalization of PCT/EP2014/070156, entitled“BLOOD PUMP CONTROL SYSTEM AND METHOD FOR CONTROLLING A BLOOD PUMP,”having an international filing date of Sep. 22, 2014, the entirecontents of which are hereby incorporated by reference, which in turnclaims priority under 35 USC § 119 to European patent application13185363.2 filed on Sep. 20, 2013, entitled “Blood pump control systemand method for controlling a blood pump,” the entire contents of whichare hereby incorporated by reference.

TECHNICAL FIELD

This document relates to blood pumps, and more particularly to bloodpumps systems for controlling a blood pump, methods for controlling aspeed of a blood pump, and methods for generating a signal indicative ofa valve state.

BACKGROUND

Blood pumps are used to provide support for the left, the right, or bothheart ventricles. These so called left ventricular assist devices(LVAD), right ventricular assist devices (RVAD) or biventricular assistdevices (BVAD) can be used to maintain the mechanical functions of theheart while a patients awaits a heart transplantation, or recovers aftera heart disease such as a myocardial infarction. In the following theabove ventricular assist devices are abbreviated by VAD. VAD systems canbe implanted, such that the discomfort for the patient is minimized. Inorder to determine how much blood needs to be pumped by the pump,methods for measuring the blood flow have been commercialized.

VAD systems often produce a flow which circumnavigates one of theheart's valves such as the aortic, mitral or pulmonary valve. However,it is desired that the heart valves functions are maintained. Thus, aneed exists to determine whether one of the heart valves opens or closesduring a heart cycle including a single systole and diastole during pumpoperation.

U.S. Pat. No. 6,066,086 discloses a method for controlling the speed ofa blood pump wherein the speed of the blood pump is controlled bydetermining a valve state of each of the atrial and mitral valves byeither the motor current or by using acoustic information of the heart.In order to determine whether said valves are open or closed, thedocument suggests an acoustic transducer to listen to heart sounds andto output a signal to a micro processor whether the valves where open ornot.

US 2010/0222634 A1 discloses a blood pump wherein the state of theaortic valve is assumed to be open when a left ventricular pressure isequal to the aortic pressure or the left ventricular pressure is greaterthan the arterial pressure. In order to measure both pressures the bloodpump includes a first sensor located at an inflow conduit and a secondsensor located at an outflow conduit. The document further assumes thatthe blood pressure at the inflow conduit in an LVAD reflects the leftventricular pressure, while the second sensor located at the outflowconduit reflects the aortic pressure. However, the method is based onthe assumption that if the left ventricular pressure was greater orequal than the arterial pressure, then the aortic valve was open.However, the state of the aortic valve cannot be reliably deduced fromthe ventricular and arterial pressure values only.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an idealized Wiggers diagram over a full heartbeat cycleand corresponding pressure difference and flow rate diagrams;

FIGS. 2a-d shows a comparison of idealized pressure difference and flowrate curves and realistic time-series pressure difference and flow ratedata;

FIGS. 3a-c shows exemplary signal characteristics derived fromtime-series data;

FIG. 4 illustrates an example of a trained classifier for classifyingthe valve state of a heartbeat cycle;

FIG. 5 illustrates a classifying scheme;

FIG. 6 illustrates a closed-loop control for a blood pump controlsystem;

FIG. 7 illustrates an aortic valve opening index over the number ofevolutions of a rotor as a moving member of a pump;

FIG. 8 illustrates an example of a sliding window approach fordetermining a current valve state index; and

FIG. 9 shows an example of a blood pump and a blood pump control system;and

FIGS. 10a, b more detailed embodiments of blood pumps.

DETAILED DESCRIPTION

Thus, the need exists for a blood pump control system and a method forcontrolling a blood pump, which may determine a valve state morereliably than previous methods. In a first aspect, this documentdiscloses a method for generating a signal indicative of a valve state.

The method includes receiving a time-series signal representing apressure difference between a first blood pressure and a second bloodpressure over at least one heartbeat cycle.

A heartbeat cycle is defined to include data of the systole and at leastthe beginning of the diastole. It is not necessary for the time-seriessignal of the heartbeat cycle to include data over various entire cyclesfrom the beginning of the systole until the end of the diastole, eventhough this is the case in several embodiments of the first aspect. Itis sufficient to receive data for each heartbeat cycle of the signalwhich includes the systole and the beginning of the diastole.

The time-series signal indicative of a pressure difference may bederived from two separate time-series signals, each signal indicative ofthe first or second blood pressure, respectively and each signalmeasured by a separate sensor. However, the time-series signalindicative of a pressure difference may also be derived from a singlesensor, such as a pressure difference sensor or a signal indicative ofan axial displacement of a rotating member of a blood pump.

Further examples of the signal indicative of the pressure difference canbe a time-series signal derived from a bearing of the pump. One exampleis a voltage time-series received from a measurement coil of an axialbearing. The position of the impeller from the measurement coil can bean almost linear function with respect to an impedance change in saidmeasurement coil; and the corresponding changes in the voltagetime-series due to the impedance change have a roughly linear relationto a pressure difference between the inlet and the outlet of the pump.While in some examples a current or voltage time-series signal from amotor of an axial pump can be used in addition to a signal indicative ofthe pressure or pressure difference, the motor current is not suited tobe the only signal used to derive a valve opening in axial pumps. Inother embodiments, the time-series signal used to derive a valve statemay be a pressure signal, such as the ventricular pressure.

The received signal is processed, and at least one signal characteristicis derived from the signal. A signal characteristic may be defined as arelationship between at least two data points of the signal or a valuederived from at least two data points of the signal, such as aderivative of the signal. The time-series signal may be processed in thetime domain and/or frequency domain. Furthermore, the time-series signalmay be processed by digital or analogue methods.

In other words, the signal characteristic extracts information from thesignal, which captures certain aspects related to a valve state andwhich reduces the number of data points used in comparison to the numberof data points of the entire time-series signal.

The at least one signal characteristic is used to classify the valvestate during the at least one heartbeat cycle. In the case of theaortic, mitral or pulmonary valve, the valve states are either “open” or“closed”. A classifying mechanism, such as a classifier, receives thederived signal characteristic and outputs an indication whether thevalve was opened or closed during the at least one heartbeat cycle.

In case of the aortic valve, the first blood pressure is the leftventricular pressure, the second blood pressure is the aortic pressure(or vice versa), in case of the pulmonary valve, the first bloodpressure is the right ventricular pressure, the second blood pressure isthe pulmonary artery pressure (or vice versa) and in case of the mitralvalve the first blood pressure is the atrial pressure and the secondblood pressure is the ventricular pressure (or vice versa).

Based on the output of the classifier a signal indicative of the valvestate is generated and a pump control system may use the signal to adaptits working parameters, particularly the motor speed. The signalindicative of the valve state may also be generated by the classifyingmechanism.

The method allows the generation of a signal indicative of a valve stateusing pump operation parameters only. Instead of needing, for example,additional acoustic transducers, a sensor system for sensing a pressuredifference is sufficient. The sensor system may be embedded in the pumpitself and in some embodiments all time-series signal data is receivedfrom sensors located within the pump housing, i.e. no additional sensorslocated outside the pump housing may be necessary, for example, externalpressure sensors attached to heart or vascular tissue directly.

In a second aspect, this document discloses a method for generating asignal indicative of a valve state as in the first aspect, but thereceived time-series signal represents a flow through the pump between aregion of a first blood pressure and a region of a second bloodpressure. Correspondingly, the at least one signal characteristic isderived from the time-series signal representing the flow. While themethod according to the second aspect utilizes a flow sensor, the methodof the first aspect relies on the pressure difference. It appears thatclassifying mechanisms using data from the method of the first aspecthave an improved success rate in classifying the signal correctly.

In one embodiment of the first and second aspects, the at least onederived signal characteristic is based on the waveform of thetime-series signal. The inventors have found that the shape of thewaveform of a signal indicative of a pressure difference or a signalindicative of the flow during the systole and at least the beginning ofthe diastole has several signal characteristics which are different foran open and a closed valve state. The waveform may contain asymmetrieswhich can be exploited to extract signal characteristics.

In a further embodiment, the at least one signal characteristic may bebased on one of the following characteristics. In the following, severalexamples of signal characteristics are given for an aortic valve.However, a person of ordinary skill in the art will understood how thesespecific signal characteristics are adapted to reflect openings of themitral or pulmonary valves.

In a first example, a difference, PULS, of a minimal, MIN, and amaximal, MAX, signal value over a heartbeat cycle may be used, thesignal being indicative of a pressure difference or a flow. It appearsthat the difference includes information whether a valve had openedduring the cycle or not. A further example of a signal characteristic isa (positive) extremal value, EXT_V, of a derivative of a signal valuebetween the minimal and the maximal value of a signal indicative of apressure difference or between a maximal and a minimal value of a signalindicative of a flow (negative extremal value). The extremal value, i.e.the highest or lowest value can be used to distinguish between heartbeatcycles with a valve opening and without a valve opening. A furtherexample is a quotient, RELPULS corresponding to PULS over MAX_N, whereMAX_N is proportional to the maximal signal value within a predeterminednumber of preceding heartbeat cycles including of heartbeat cyclespreceding including the first heartbeat cycle. Another example is thetime interval, DUR, between a minimal value and an intersection point oftwo tangent lines, the first tangent line being a horizontal linethrough the data point corresponding to the minimal value and the secondtangent line running through the data point of the signal, at which thederivative has an extremal value (see above). A further example is anangle, ANGLE, between the tangent line through an extremal point and aline through the time-series values at the beginning and a value of thetime-series signal corresponding to an end value of the interval DUR. Afurther example is the area, AREA, between the two tangent lines and thesignal values. These signal characteristics on their own, in combinationor in combination with further signal characteristics may be used toclassify the valve state of the at least one heartbeat cycle reliably.In a further embodiment, the chosen signal characteristic is AREA andoptionally at least one further signal characteristic.

The above examples do compare values of data points of the signal toother data points of the signal, thereby reducing the effects oftrending which are frequently found in human physiologic data and whichoften affect the data values, but not the content found within the data.This improves the reliability of the classifier. However, other signalcharacteristics, such as the sign of the value of the data points cansupplement the previous values derived from a comparison of values ofdifferent data points within one or several heartbeat cycles.

Consequently, when more than one signal characteristic is derived fromthe time-series signal, the classification may be based on more than onesignal characteristic.

In a further embodiment, the time-series signal over at least oneheartbeat cycle is analyzed and, if necessary, is separated into signalfragments, i.e. subsets of signals, where each signal fragment or signalof a subset includes data from one heartbeat cycle only. Additional datamay be discarded in some embodiments. The separation may positivelyaffect the quality of the results of the classification process.Furthermore, when extracting signal characteristics, it might bebeneficial to preanalyse the signals by separating the signal intosignals including a single heartbeat only or to separate signal segmentsand to detect the points of interest before forwarding the signalcharacteristics to a classifier, to improve the quality of the results,tests can be conducted to test whether the signal segments or thedetected point of interest have been detected and segmented correctly.Such tests can be based on separated classifying system.

As will be discussed later within this document, the signalcharacteristics may be derived from heartbeat cycles of which the valvestate is known. The trained classifier may then classify based on one ormore of the selected signal characteristics.

In a third aspect, this document discloses a method for training aclassifier for classifying a time-series signal regarding a valve state,each signal indicative of a pressure difference or a flow or at leastone signal characteristic derived from said signals.

To train the classifier, a first group of time-series signals, eachsignal representing data of at least one heartbeat cycle when a valvestate was open, and a second group of time-series signals representingdata of heart, each signal representing data of at least one heartbeatcycle when a valve state was closed, are generated.

The signals of the first and second groups may be recorded from patientssuffering from conditions similar to the conditions of patients havingan implanted VAD device. The signals are further analyzed and classifiedby a physician as open or closed. Alternatively, the signals of thefirst and second groups may be recorded from patients having animplanted VAD device and to simultaneously record the heart sounds by anacoustic transducer. Heart sounds allow a reliable classificationwhether a valve, such as the aortic, pulmonary or mitral valve was openor closed. In a further embodiment, the signals of the first and secondgroups may be recorded while simultaneously using ultrasound imaging todetermine whether the valve state was open or not. The ultrasoundrecordings are used to identify whether a heartbeat cycle belongs to thefirst and second group. Matching the time-series signals and thecorresponding heart sounds allows a very reliable classification of thesignals.

After the time-series signals have been labelled as “open”, “closed” or“unknown”, in case no reliable conclusion can be made, at least onesignal characteristic is derived from each of the signals of the firstand second groups.

The at least one signal characteristic is then used to train aclassifier to discriminate the valve states between, for example, “open”or “closed”. Additional states, such as “probably open” or “probablyclosed” or “unknown” may also be considered.

For example, several classifiers described in the prior art can bechosen. As examples, the classifier to be trained may be a neuralnetwork, a support vector machine, a Gaussian classifier, a Naïve Bayesclassifier, a decision tree classifier or a k-nearest neighbourclassifier. Various other classifiers types, such as other linearclassifiers or non-linear classifiers may also be used.

After the classifier has been trained as described above, the classifiermay be used in one of the methods of the first or second aspect as aclassifying mechanism. The trained classifier may be implemented as aset of machine-executable instructions such as software, firmware orhardware or electronic circuitry. The methods of the first and secondaspects may also be implemented as computer-executable software,firmware or hardware or electronic circuitry or a combination thereof.Furthermore, the methods may be implemented in a blood pump, a systemincluding a blood pump or a blood pump controller as electroniccircuitry, computer hardware, firmware or software, or a combinationthereof. These encompass processor-executable programs,processor-readable set of instructions and the like.

In a fourth aspect, this document discloses a blood pump control systemincluding means for receiving a time-series signals indicative of apressure difference. These means can include signal detection circuitrylocated in the pump or a control system for the pump or a signal databus between a pump and a control system for the pump.

The system further includes a signal characterizing circuit for derivingat least one signal characteristic from the time-series signal. Thiscircuit may include a microcontroller or a processor configured foranalyzing the signal, optionally dividing the signal in subsets ofsignals, for example so that each signal of a subset only includes asingle heartbeat cycle, and deriving at least one signal characteristicfrom the time-series signal or the signals of the subset.

The at least one derived signal characteristic (which may represent onlya small amount of data compared to the data of the entire time-seriessignal or of each signal of the subset) is input into a classifyingcircuit, which may include separate components or components also usedin the signal characterizing circuit. The classifying circuit includes aclassifying routine such as the described trained classifier, forexample, to classify the signal or each of the signals of the subset tocorrespond to a heartbeat cycle with an open valve or a closed valve. Inthis sense “closed” can be understood as “not open” but can includeseveral states such as “probably closed” or “unknown”. The classifyingmechanism analyzes the at least one signal characteristic and outputs asignal indicative of the valve state. This signal can include theupdating of a counter, the updating of a counter during a running timewindow, or can apply a label to each time-series signal, the signalcorresponding to the respective valve state.

However, the output signal of the classifying may also be used by afurther circuit to generate a signal indicative of the valve state basedon the output signal.

In one embodiment, the signal indicative of a valve state is used toconstruct a valve state index, VSI, which may, for example, be a valveopening index, VOI, relating the number of occurrences of an open valvestate in the classified signals to the number of classified signals or avalve closing index, VCI, relating the number of occurrences of a closedvalve state in the classified signals to the number of the classifiedsignals. The VSI may be used as a part of a control loop to adjust thespeed of a movable member of a pump, for example, a rotor, a piston or amembrane.

The VSI can be kept in a memory and may be updated by further signalsindicative of a valve state. The VSI may be constructed by calculatingthe VSI from available signals indicative of a valve state. For example,a plurality of signals indicative of a valve state may be stored inmemory and values stemming from older signals may be deleted for valuesfrom newer signals to have an indication of an actual VSI, reflectingthe index over a predetermined number of previous heartbeat cycles or apredetermined length of time.

The actual VSI may be compared to a target VSI and the speed of the pumpmay be adjusted based on the comparison of the actual and target VSIvalues. For example, in case the VSI is a VOI, a reduction in speed maybe necessary if the VOI indicates that the valve does not open asufficient number of times over a predetermined number of heartbeatcycles to result in a desired therapeutic effect of the pump operation.In case of a VCI, the reduction may take place if the valve is closedtoo many times.

Whether a VOI or a VCI is used may depend on the choice of the medicalpractitioner or a desired therapeutic effect. For example, the chosenclassifier may have an effect on the sensitivity or specificity forcorrectly classifying open or closed valve states. Depending on whethera high specificity or sensitivity is desirable a VOI or VCI may bechosen.

A further aspect of the application is a method for controlling a speedof a pump by constructing a valve state index, VSI, of a valve from aplurality of signals indicative of a valve state of the valve andadapting the speed of the pump based on the VSI. Preferably the signalsindicative of a valve state are time-series signals, which are analyzedby a method or system as described above.

Many pumps can use a pulsatility index, PI, for the operation of a pump.However, the PI is often based on measurements of pressure, motorcurrent, pressure differences or the like and, in this sense, do notdirectly correspond to a physiological phenomenon. Furthermore, theconstructing of a VSI can be performed on heartbeat cycle time-seriesdata and the additional knowledge which valve state occurred for anumber of the heartbeat cycles. The pump operation is thereby adapted toeach patient individually.

Using a valve state index has the benefit of relating the pump operationto the physiologic effect of the valve opening and closing. An index isin one embodiment understood as a quotient of a first number ofheartbeat cycles and a second number of heartbeat cycles out of thefirst number of heartbeat cycles, the second number representing thenumber of occurrences of a chosen valve state, e.g. an open or closedvalve state. An index defined as above represents a percentage of thechosen valve state occurring compared to all valve states occurring.

In a further embodiment, the VSI may be updated on the fly, i.e. usingvalve state indications which were determined after an initial or firstconstruction of the VSI. For example, the oldest valve state indicationsmay be dropped for newly determined valve state indication therebyrepresenting an actual or current VSI based on date from a predeterminedtime interval only or from a predetermined number of valve stateindications only.

The updating can, for example, be performed for every new valve stateindication, for every fifth, tenth or hundredth valve state indication,for every new occurrence of a chosen valve state indication or, forevery fifth, tenth or hundredth chosen valve state indication, or for apredetermined time interval, such as updating the VSI by using valvestate indications recorded during a past second, minute or 10 minutes,for example, using the new data in addition to previous data from aminute, five minutes, ten minutes or one hour prior to the new valvestate indication data. The regular updating reflects the current VSI butsmoothes the occasional, irregular behavior, such as an unexpectedperiod of the chosen valve state not occurring, even though it would beexpected under normal circumstances.

In a further embodiment a predetermined total number of valve stateindications from heartbeat cycle time-series data is used, such as 50,100, 200, 350, 1000 or more are used to determine the valve state index.This can reduce the amount of data that needs to be stored forcalculating and constructing the index.

In a further embodiment, the VSI may be used as a part of a closed-loopcontrol system. After determining the current VSI, the speed of the pumpmay be adapted to increase or decrease the VSI to a desired target VSI.For example, if the chosen valve state is an open valve state of theaortic valve, i.e. the VSI is a valve opening index, VOI, then a low VOImay indicate that the pump transports too much blood for the valvehaving to open. Consequently, in some therapeutic programs, the speed ofthe pump would be reduced to increase the VOI to a target VOIrepresenting valve activity due to a reduced pumping speed.

In a further embodiment, additional valve state indications are derivedbased on measurements of a pressure, or pressure difference, or a flowthrough the pump after the speed has been adapted to check whether thecurrent VSI is closer to the target VSI. In some embodiments, thepredetermined time interval or predetermined number of heartbeat cyclesmay be changed from an initial, larger number to a smaller number (orvice versa) depending on how far the current VSI is away from the targetVSI. For larger required or desired changes of the current VSI to atarget VSI, a smaller time interval or a smaller number of valve stateindications may be desired, since the VSI then reflects more currentevents.

Furthermore, in some embodiments, the target VSI is not a singlenumerical value, but an interval. This has the benefit of the systembeing allowed to operate within a range of target VSIs, thus, reducingthe need to constantly adapt the speed of the pump in a closed-loopcontrol. The interval may be chosen as an open or a closed interval.E.g. the interval may have a range of less than 0.1 or less than 0.05 ofan index running between 0 and 1.

A further aspect of this application is a system for a control of ablood pump, including a control unit including means for receiving asignal indicative of a valve state of a blood system valve. The meansmay be an analogue or digital signal processing circuit, for example.The system further includes a signal processing circuit configured forcalculating a VSI based on the received signals. The signal processingcircuit may be the same as the means for receiving the signal indicativeof the valve state. Furthermore, the control unit is operably connected(via cable or wirelessly) to a motor controller connected to a motor ofa blood pump, the speed of which may be adjusted based on the VSI.

In case the pump system also includes means for measuring a signal, suchas a pressure difference, from which the control unit or a further unitmay derive a signal indicative of a valve state, then the control systemmay be designed as a closed-loop control system.

In a further embodiment, the system may also include the blood pumpincluding a motor, an inflow and an outflow conduit and a movableelement for producing a flow between the inflow and outflow conduit,such as a rotor, a piston or a movable membrane.

In a further embodiment, the system may also include a comparatorcircuit configured for comparing a current VSI to a target VSI, and asignal processing circuit for receiving a comparator signal and sendinga signal to the motor controller to adjust the speed based on thecomparator signal. This comparator circuit is helpful for an automatedclosed-loop system.

Further aspects or embodiments can be derived from the claims or thefollowing description of specific embodiments shown in the figures. Itis noted that the specific embodiments show more elements than arenecessary for the operation of the methods or the systems described bythe invention. Consequently, elements shown in the Figures or describedin the accompanying description may be claimed on their own at a laterstage in the proceedings. Additionally, element(s) shown in one specificembodiment may be combined with element(s) shown in a differentembodiment.

In a further aspect, a blood pump comprises a hollow body, in which animpeller with a blading is provided, for the production of an axialpropulsion of the blood along the impeller, as well as at least partlyactively stabilised axial magnetic bearing device and preferably, butnot necessarily a hydrodynamic bearing device for the impeller, whereinthe impeller may be set into a rotation about a rotation axis of theimpeller, with a motor stator preferably but not necessarily locatedoutside the hollow body, and wherein the hollow body comprises an inletfor the flow of blood into the hollow body in an inflow directionessentially parallel to the rotation axis, and an outlet for the flow ofthe blood out of the hollow body in a flow-out direction. Preferably,but not necessarily, the outlet is arranged offset with respect to therotation axis of the impeller for producing an outflow angle between theinflow direction and the outflow direction, which is different fromzero.

According to an embodiment, on the upstream-side and on thedownstream-side of the impeller permanent magnet arrangements areprovided and the pump has at least one actuator ring coil for activelystabilising the impeller in axial direction. In some embodiments, thereis only one actuator coil.

The single actuator ring has several embodiments which make sure thatthe impeller is always stabilised in the axial direction.

According to a first embodiment, the only (one) actuator ring coil actson both, the upstream-side and the downstream-side permanent magnetarrangements by using an iron yoke for transferring the magnetic flux toat least one of the permanent magnet arrangements, wherein the actuatorring coil acts directly on the remaining magnet arrangement.

In a second embodiment, the at least one actuator coil acts on only afirst of the upstream-side or downstream-side permanent magnetarrangements and the other permanent magnet arrangement is configured asa passive axial bearing. Possibly, but not necessarily, this passiveaxial bearing arrangement comprises two magnets which attract each otherand act as a ‘spring’ in order to pull the impeller in the desireddirection. In this case, the thrust caused by the magnetic flux of thesingle actuator acts against the force of the spring.

In any of these axial stabilising arrangements, only one or,alternatively, both of the upstream-side and downstream-side permanentmagnet arrangements of the impeller comprise a sensor system fordetecting a possible deviation of the impeller from a desired axialposition. In an embodiment, the at least one sensor system interactswith the actuator ring coil for correcting a possible deviation of theimpeller from the desired axial position.

As will be described in further detail below, an inner radius of thehollow body is enlarged for forming a discharge channel which runstangentially around the impeller and runs out into the outlet, for aflowing-away of the blood out of the hollow body, running essentiallytangentially to the impeller. Preferably, but not necessarily, thecentre of the discharge channel offsets away from the impeller in adirection axially to the rotation axis of the impeller. Thus, thedischarge channel has similarities with a ‘snail shell’ as it preferablynot only continuously widens its cross section, but has a (preferablycontinuously growing) offset in the direction of the rotation axis ofthe impeller.

In some embodiments, the impeller includes a support ring, which formsan annular gap (or several annular gaps) between the support ring and aninner wall of the hollow body. Such a support ring, preferably formed asa rotationally-symmetrical hollow cylinder, may be designed in differentwidths and may be fastened on the impeller at any location, in order toachieve an optimal stabilisation of the impeller, in particular withrespect to tilting of the impeller. In this manner, one may compensateimbalances of the impeller in a particularly effective manner. thiscase, a suitable support ring directly upstream of the discharge channelin the flow direction, may contribute to a stabilisation of theimpeller.

The pump may comprise a blood pump control system as describedthroughout this application or may incorporate a method of adapting thespeed of the pump as included herein.

FIG. 1 shows a Wiggers diagram in the top panel and corresponding,idealized diagrams of a pressure difference between an aortic pressureand a left ventricular pressure (middle panel) and a diagram of a flowrate through the ventricle (bottom panel) during a heartbeat cycle overtime. All pressures are shown in the unit of mmHg and the flow rate isshown in the unit of ml. The curves are representative of a human heart.

The top panel shows an idealized pressure curve of the aortic pressure1, the left ventricular pressure 2 and the left atrial pressure 3. Attime t0, the mitral valve closes and causes an isovolumic contraction upto time t1, at which the aortic valve opens. Subsequently, the leftventricle starts ejecting blood into the aorta until the aortic valvecloses at time t2. The time between the closing of the mitral vale andthe closing of the aortic valve is the systole. The left ventriclerelaxes isovolumetrically until time t3, at which the mitral valve opensagain, causing a rapid inflow of blood into the left ventricle. Therapid inflow slows down during the diastole starting at t4. With theatrial systole starting at t5, the filling of the ventricle terminatesat t6, at which the mitral valve opens again, ending the heartbeatcycle.

The middle and bottom panels show the pressure difference 4 and the flowrate 5 during the heartbeat cycle. Shortly, after the opening of theaortic valve the pressure difference reaches a pressure differenceminimum a. From the minimum, the pressure difference rises slowly untilthe closing of the aortic valve at time t2. After time t2, the pressuredifference rises rapidly to a maximum dl at time t3. The pressuredifference thereafter drops slightly until the eventual closing of themitral valve again.

The corresponding flow rate 5 looks almost like a mirrored curve of thepressure difference. The flow rate rises slightly until the opening ofthe mitral valve and then rises rapidly until the opening of the aorticvalve. The flow then remains high and slightly drops before droppingrapidly after the closing of the aortic valve until the opening of themitral valve.

In FIGS. 2a and b , the pressure difference 4 and the flow rate 5 areshown again. However, FIG. 2c and FIG. 2d show a more realistictime-series data of the pressure difference and the flow rate,respectively. It is easily understood that the idealized curves aremerely illustrative. However, certain points of interest can be detectedin the realistic time-series data, such as the minimum or maximum of thedata values of the time-series.

In FIG. 3a an example of a time-series signal of a pressure differencewith an opening aortic heart valve is shown, where the time-series shownin FIG. 3b is representative of a heartbeat cycle in which the aorticvalve stays closed. The two time-series shown in FIGS. 3a and 3b doinclude noise or sampling effects. The difference is particularlyevident during the ventricular systole and the isovolumetric relaxationof the ventricle. The inventors have found that while the maximal andminimal values may vary between heartbeat cycles with an opening aorticvalve and a closed aortic valve, the PULS of heartbeat cycles with aclosed aortic valve vary not too much between different heartbeat cycleswith a closed cycle and they are comparatively smaller than the PULS ofheartbeat cycles with an open aortic valve. These effects are bettervisible when looking at the pressure difference, in contrast to theminimal or maximal values of the pressure time-series, which are notwell suited to construct a reliable classifying scheme to determinewhether the aortic valve was open or closed during a particularheartbeat cycle.

Looking at the pressure difference time-series improves the reliabilityfor correctly determining the valve state, e.g. open or close. However,while the absolute values of points of interests, such as the minimal ormaximal values of the pressure difference (or flow rate) have a positiveeffect on the reliability, looking at at least one different signalcharacteristic may greatly improve the reliability of the classifyingstep or the classification overall.

FIGS. 3a and 3c , besides the time-series data, indicate the minimumvalues a, the maximal values d, as well as tangent line through minimuma (i.e. a horizontal line) and a tangent line through an extremal valuedata point b between values a and d, i.e. a tangent through the value ofthe extremum of the derivative of the time-series. Furthermore, the areawhich is bordered by the two tangent lines and the time-series isdepicted as a filled area.

In the chosen data samples it is easy to see that the AREA of an openvalve and of a closed valve state are significantly different from eachother (among others). Hence, by deriving signal characteristics from thecurve that go beyond the absolute values of the time-series (i.e.higher-order signal characteristics), it becomes easier to identifydifferences between heartbeat cycles with an opening aortic valve andheartbeat cycles with a closed valve.

FIG. 3c shows the time-series values, the minimal value a, thehorizontal line and the tangent line running through extremal value b,the area, AREA, bordered by the tangent lines and the time-series, anangle α, ANGLE, between the tangent line running through extremal valueb and a line through the time-series values at the beginning, i.e.through point a and a value c of the time-series signal corresponding tothe end of the interval DUR. While these are some examples ofhigher-order signal characteristics, other examples may be envisioned.For example, corresponding data characteristics may be derived between amaximal value before or right after the start of the ventricular systoleand the minimal value a.

It has been found that AREA for heartbeat cycles including an aorticvalve opening is, on average, larger than the corresponding area of aheartbeat cycle with a closed aortic valve. Furthermore, the timeinterval between the time of the minimal value a and the intersectionpoint of the two tangent lines is, on average, larger for heartbeatcycles with an opening aortic valve than for a heartbeat cycle with aclosed aortic valve.

Further examples of higher-order signal characteristics are a differencebetween a minimal value a and a maximal value d. As a further example ofa signal characteristic involving more than one heartbeat cycle, adifference between a minimal value of a current heartbeat cycle and themaximum of the maximal value d of a number of past heartbeat cycles maybe derived. The number may be predetermined or random. The number canbe, for example, between 2 and 10. The signal characteristics may benormalized to their respective heartbeats, e.g. the numerical valuesobtained fro the signal characteristics can be divided by the length ofthe heartbeat cycle. This may be an improvement when comparing differentdata to derive the valve state of a heartbeat cycle.

While a single signal characteristic may improve reliability ofdetermining a valve state, analyzing several signal characteristics andusing these signal characteristics during classification of online datamay further improve the reliability.

The time-series data is pre-processed and in some embodiments sampledand/or separated in sets of subsignals, each subset comprising only onefull heartbeat cycle. However, the derivation of signal characteristicscan also be performed on time-series including more than a singleheartbeat cycle.

Thereafter, a signal processing circuit or signal processing softwaredetermines particular data points, for example minimal, maximal andextremal values, by known signal analysis routines. From the determinedvalues the signal characteristics are constructed and used forclassifying the heartbeat cycle from which the signal characteristicswere extracted. Thus, the time-series data of the pressure differencesignal of a heartbeat cycle, which may be large, is collapsed to a smallset of data points describing the signal characteristics to be used forclassifying and in some embodiments a time stamp or a identificationnumber. The small set of data points including the one or more signalcharacteristic and a time stamp or identification number can be used todetermine the valve state for each heartbeat cycle. The determined valvestate (i.e. signal indicative of the valve state can be used to controlthe pump operation by maintaining, increasing or reducing the speed ofthe pump depending on the target range of a valve state index, i.e.depending on whether the current valve state index is equal, below orabove the desired target range.

In the above embodiment, the time-series data of the pressure differenceor flow rate is reduced to a vector representing signal characteristicsand higher-order signal characteristics of the time-series, in someembodiments keeping a single vector per determined heartbeat only. Thisvector may then be further reduced to a single value indicating whetherthe valve state was opened or closed when the vector is entered into thechosen or trained classifier. However, it is also possible to derive avector of signal characteristics and derive the valve state from saidvector directly instead of saving the vector and deriving the valvestate by feeding the vector to the classifier at a later point in time.While some embodiments may keep timing information, other embodimentsmay not keep timing information, but only information whether the valvewas open or closed for a specific heartbeat. The exact opening orclosing times of the valve may not be necessary in those embodiments.

Even though, in the embodiments discussed so far only one type oftime-series signals is analyzed and signal characteristics are extractedfrom this one type of signal. However, signal characteristics can alsobe extracted from more than one time-series signals types. By means ofusing signal characteristics of more than one type of signal the overallaccuracy of the classification may be improved.

It is noted that the partitioning of heart time-series data into subsetsof data containing a single heartbeat cycle only are well known in theart, e.g., the local minimum of the pressure difference curve can bedetected. Alternatively, methods known from the signal processing ofelectrocardiograms can be used. Furthermore, the methods, systems andapparatuses discussed in this document may include methods for samplingand preprocessing time-series data, such that the time-series data canbe analyzed and a valve state may be determined.

FIG. 4 shows a schematic overview of how a classifier can be trained andhow a trained classifier can be used to derive a valve state from actualtime-series data to be analyzed, e.g. live online or stored time-seriesdata.

FIG. 4 illustrates an embodiment of a method of training a classifierwhich may be used for classifying heartbeat time-series data.

The method 100 of training a classifier 110 includes the selection ofsignal characteristics from at least one type of time-series signalsrepresenting data recorded over one or more heartbeat cycles.

In the present embodiment, the classifier includes 5 signalcharacteristics including the difference between a maximal and a minimalvalue of time-series data of a pressure difference between the leftventricle and the aorta. This signal is well suited for training aclassifier to classify whether the state of the aortic valve during aheartbeat cycle was open or closed. However, different signals can bechosen such as a pressure difference between the right ventricle and thepulmonary artery which is well suited to classify the state of thepulmonary valve or a pressure difference between an atrium and thecorresponding ventricle which is well-suited to classify the state ofthe mitral valve connecting the atrium and the ventricle. Furthermore,the signal could in some embodiments also be a flow rate through a pump.In other embodiments a ventricular pressure may be used as the signal toderive the valve state during a heart beat. This may be the case, if thesignal shows similar higher order signal characteristics as the signalindicative of the pressure difference and if those higher order signalcharacteristics (or any one of the signal characteristics) correlatewith the valve state.

In the present example, the time-series data has already been dividedinto subsections which contain data from a single heartbeat cycle only.In FIG. 4 the data set of time-series data of heartbeat cycles duringwhich the aortic valve was closed is denoted by reference sign 120, thedata set of time-series of heartbeat cycles during which the aorticvalve opened is denoted by reference sign 130. Both data sets 120 and130 contain several subsections 121 and 131, respectively. The divisioninto several subsections may be performed by a signal preprocessingcircuit or algorithm 140. The preprocessing of the subsections or thetime-series data in general may further include standard procedures suchas high, low or band-pass filtering, sampling of analogue recorded dataand the like. A plurality of subsections 121 and 131, respectively isprocessed by a signal characterizing circuit or by a signalcharacterizing algorithm 150, which derives at least one signalcharacteristic 151 from the subsection to be analyzed. Further signalcharacteristics 152 through 155 may be derived by the same circuit oralgorithm or, in other embodiments, by additional circuits oralgorithms. For each of the plurality of subsections the one or moresignal characteristics 151 through 155 are derived. In the embodimentdescribed by FIG. 4, the signal characteristics 151 through 155 aregrouped as a vector 156. This vector 156 is used to train the classifier110, however, the classifier may also be trained by additional vectorsand/or by not using each and every entry of a vector. The classifier isa Naïve-Bayes classifier and is trained to recognize a differencebetween the data sets 120 and 130, so that real data can be classifiedreliably by the trained classifier. Since it is assumed to be known foreach subsection whether the subsection include a valve opening or nor,it is possible to train the classifier to correctly classify data forwhich the valve state is not known. From the theory and mathematical orexperience background of the chosen classifier it can be estimated howmany subsections are necessary from each data set to obtain a trainedclassifier having a desired confidence interval of the specificity andsensitivity or reliability. The reliability criterion may be formulatedto correctly classify the real data in more than 70% or more of allcases. The specificity and sensitivity criteria take into account thatsome applications of the classifier may use said classifier to be surethat the presented data was of a heartbeat cycle with an open or closedvalve, respectively, i.e. reducing the number of false positives orspecificity. The same applies to the sensitivity which aims at reducingthe number of false negatives. However, when applying these criteria ithas to be decided whether the open or closed state is a positive ornegative in order to determine a false positive or negative.

The classifier 110 is a hard-wired, software or firmware-based algorithmwhich is trained by using time-series data from signals includingheartbeat cycles for which the valve state (in this case the aorticvalve) is known. The trained classifier may be uploaded into a signalclassifying circuit or algorithm 160 and then be used to classify realdata.

This is further illustrated by the application of the trained classifierto real time-series data 170 of a signal type corresponding to thesignal type(s) used in data sets 120 and 130 which has been preprocessedinto subsections. For each subsection 171, one or more signalcharacteristics 151 through 155 may be derived or extracted. Thesesignal characteristics need to include the signal characteristics whichwere used to train the classifier 110. The trained classifier 110 readsthe vector 176 and classifies it as representing a heartbeat cycleincluding a valve opening, OPEN (180) or not, CLOSED (190).

Both, the training of the classifier and the application of theclassifier, can be performed using the circuitry of a single pump.However, the training of the classifier may also be performed externallyand the trained classifier may then be uploaded into the control systemof the blood pump.

While in this embodiment only a single classifier was used, otherembodiments may use more than one classifier, the further classifierspossibly being classifiers of different types, such as a support vectormachine, a k-nearest neighbor operator or a neural network (feed-forwardincl. hidden layers or nor e.g.). Furthermore, since the differentclassifiers have different strengths and weaknesses an approachemploying several classifiers may increase the reliability of theclassification. Additionally or optionally, the further classifiers mayoperate on a range of different signal characteristics. The combinationof processing different signal characteristic by different classifiersmay also increase the reliability of the classification in someembodiments.

FIG. 5 illustrates a schematic overview of a classification scheme 200.In a first, optional step, the classification scheme receives atime-series signal of a flow rate between the right ventricle and thepulmonary artery. This signal is also preprocessed such that subsectionsof the signal include data from a heartbeat cycle only. From this datasignal characteristics are derived in a step 210. These signalcharacteristics are fed to a trained classifier in a further step 220.The trained classifier labels the heartbeat cycle with a label of anopen pulmonary valve or a closed pulmonary valve, i.e. into an open orclosed state heartbeat cycle. It is noted that once a subsection of atime-series has been used to derive the valve state of said subsection,the data of the subseries is no longer necessary with respect todetermining the valve state and in some examples may be discarded.However, in further examples the data may be stored in cases where theclassifier can only classify the valve state of the heartbeat cycle by asmall margin. This data subsection may later be used to improve thetrained classifier, for example.

The inventors have found that, particularly in the pressure differencecurve, a significant deviation is present between heartbeat cycles inwhich the aortic valve opens and in which the aortic valve remainsclosed.

The previous drawings helped to illustrate how different heartbeatcycles may be classified to represent an episode with an open or aclosed valve. This classification may be used to control a blood pumpsystem as will be illustrated with the help of FIGS. 6 through 8.

FIG. 6 illustrates a closed loop control system 300 of a blood pumpsystem. The operational parameter to be controlled is the speed of thepump. Even though many different parameters may be operated, in thepresent embodiment, the pump is an axial flow pump with an outlet whichis at a non-zero, preferentially 90°, angle to the axis of the axialflow pump. Examples of an embodiment of such a pump can be found in U.S.patent application Ser. Nos. 13/505,368, 14/115,425 or U.S. Ser. No.14/115,460 which are incorporated herein in their entirety. Morespecifically, some embodiments include a rotor which, at least whenrotating, is suspended between two hubs which border the rotor in anaxial direction on both sides. However, the following control method mayalso be used with other types of axial flow pumps or turbo pumps, i.e.rotational or centrifugal pumps.

In the present embodiment the parameter to be controlled is therotational speed n of an impeller of the pump. The measured output ofthis particular embodiment is the distance 310 of the rotating impellerfrom a hub. This distance is proportional to a pressure differencebetween an outlet of the blood pump and an inlet of the blood pump. Inother words, while the measured variable in the present embodiment isnot the pressure difference itself, a variable which is proportional tothe pressure difference is measured. However, other embodiments mayinclude measuring the pressure difference by employing a sensor in thearea of the outlet of a blood pump and a further sensor in the area ofthe inlet of the blood pump. The pressure difference is translated intoa time-series signal, which is divided into subsections representingtime-series data of a heartbeat cycle only. These subsections areprocessed and a classifier 320 as described previously in thisapplication is used to derive the valve state of the subsection.

The valve states and/or their occurrence in time are used toconstructing an aortic valve opening index (AVOI) as an example of avalve state index (VSI). The AOVI 330 represents the percentage ofheartbeat cycles with an open valve compared to all analyzed heartbeatcycles. The index has no dimension. In other embodiments, the index maybe a closed valve index representing the percentage of heartbeat cycleswith a closed valve state.

The AVOI 330 may be constructed in different ways. In some embodimentsthe AVOI may be based in the 10, 20 or 50 past heartbeat cycles.Additionally, several AVOIs may be constructed representing differenttime scales. While using more heartbeat cycles makes the index lessprone to random events, using fewer cycles has the effect of moreaccurately describing the current state of a patient. The AVOI which isconstructed from sensed data and which is used to control the pump willbe referred to as AVOI or current AVOI. In contrast, a target AVOI is anAVOI value to which the current AVOI should adapt to due to a speedadaptation.

The mode of operation is controlled by an AVOI controller 340 and can beset externally. Different exemplary modes of operations are described inconnection with FIG. 7, even though the subject matter is not limited tothe modes described therein. The AVOI controller receives a current AVOI341 from the AVOI constructing entity 330 and has been set externally toa mode of operation 342 which corresponds to a target AVOI 343. In thepresent example, the rotational speed of the pump is increased when thecurrent AVOI is higher than the target AVOI and the speed of the pump isreduced when the current AVOI is smaller than the target AVOI. Theadaption of the speed of the pump is controlled by controller 340. Thecontroller may be a microprocessor, a programmable field-array, amicrocontroller or software or firmware kept in a memory and processedby a processor such as described above. In a chosen example, the currentAVOI is higher than the target AVOI and the speed of the pump isincreased. The time it takes for an increase of speed to show in thecurrent AVOI depends on the method of constructing the AVOI and theheart rate in some embodiments.

In this embodiment, the AVOI depends on the speed of the blood pump asis illustrated in FIG. 7. In the plot of FIG. 7, an AVOI in dependenceon the number of rotations per minute, n, for a specific pump are shown.The dimension of n is kilo rounds per minute or krpm. The differentcurves shown in the plot refer to different values of the maximal valueof the elasticity at the end of the systole, E_max. The two curves 350and 360 correspond to a smaller and a larger value of E_max,respectively. It can be seen that the curve 350 corresponding to a smallE_max value is flatter, while curve 360 corresponding to a larger E_maxvalue has a more sigmoidal shape. In other words, different patients'hearts react differently to a change in the pump speed in that thechange of the AVOI is different. However, each curve can be representedby a bijective function in that each value of n can be mapped to adifferent value of AVOI and vice versa.

The plot further shows a n-AVOI pair referring to a partial assist mode,PA, and a full assist mode, FA. These value pairs are of interest insome embodiments of the subject-matter of this application. The FAdiffers from the PA in that the aortic valve is permanently closed andonly opens sporadically, if at all. In the plot of FIG. 7, the AVOIs arebelow 10%. The full assist mode offers a mode for allowing heartrecovery without putting external stress on the heart since the pump isfully responsible for the pumping of blood. This is in contrast to thePA, which intends to let the heart do some, but not all of the pumping,so the heart can slowly recover to being able to pump the blood on itsown. The FA mode may be further described by a maximal pump flow rate, asmall LVEDV, a small LVSV, little movement of the myocardium, a smallpulsatility of the aortic pressure, minimal external work and a minimalpressure-volume-area.

The PA mode of pump operation may be described by partially assistingthe heart in its pumping operation. In particular, when the pump pumpsbetween the left ventricle and the aorta, the aortic valve opens atleast some of the heartbeat cycles, i.e. the AVOI is non-zero, but maybe between 20% and 40%. For the chosen values of E_max, the AVOI is PAmode is around 34%. Physiologically, this means that the ventricle stillcontributes to the pumping operation, which is indicated by the sporadicopening of the aortic valve. In different embodiments, the PA mode maybe described by at least one of allowing a moderate pump flow rate (i.e.the pump does not contribute 100% to the flow rate between the ventricleand the aorta), a moderate left ventricular end-diastolic volume, LVEVD,a moderate left ventricular stroke volume, LVSV, a moderate movement ofthe myocardium, a moderate pulsatility of the aortic pressure, anincreased external work by the heart itself, an increasedpressure-volume area in a pressure-volume diagram. Furthermore, in thepartial assist mode suction of the heart wall upon the inlet of the pumpshould not occur or only rarely occur.

For example, it is assumed that an implanted pump is operating within apatient whose heart has an E_max value comparable to the E_max value ofcurve 350. The pump includes a pump closed-loop control system asillustrated in FIG. 6. The current AVOI of the patient is 60% at about 6krpm. The selected mode of operation is a PA mode, which corresponds toan AVOI in an interval between 30% and 35%. The interval can be madebigger or smaller in other embodiments, and as an effect of how fast thetarget AVOI can be reached and how often the speed needs to be adapted.A smaller interval usually requires a speed adaption more frequentlythan a bigger interval.

Different methods of updating an AVOI, or different VSIs, are explainedin connection with FIG. 8. The shown embodiment illustrates a slidingwindow approach of updating the AVOI. The sliding window 400 has a widthof 10, 20, 50 or more valve state indications 410. A valve stateindication 410 denoted by “C” refers to a heartbeat cycle which wasclassified as a closed valve cycle and by “0” refers to a heartbeatcycle which was classified as an open valve cycle. If the different openor closed valve cycles are indexed by time, the times between differentcycles may vary due to changes in the heart rate of the patient, forexample. In the present example, the AVOI is constructed by using the,for example, past 50 valve state indications from the time ofcalculating the current AVOI. In other words, when a new valve stateindication is generated, this valve state indication is used togetherwith the preceding 49 valve state indications to derive the currentAVOI. The valve state indication preceding the latest valve stateindication by 50 indications is no longer used for constructing the AVOIand may be deleted from a memory in which the values used for the AVOIconstruction are stored. This memory may be volatile or non-volatile andcan be part of a main memory of the pump control system, for example. Adifferent embodiment of constructing the AVOI is to reconstruct the AVOIevery, for example, 30 valve state indications using these 30 valvestate indications only. In further embodiments, the AVOI constructionmay also include the preceding 30 valve state indications. Instead ofcounting the number of occurred valve state indications, the AVOI mayalso be reconstructed after a predetermined interval of time, such as30, 45, or 60 seconds, regardless how many valve state indications havebeen generated in this interval. In further embodiments, the number ofopen or closed valve indications may be counted and the AVOI may bereconstructed after this preset number of open or closed valve stateindications. Furthermore, in other embodiments, the AVOI may beconstructed by using a sliding window approach, however, instead ofreconstructing the AVOI after each new valve state indication, the AVOIis reconstructed after each 10^(th), 20^(th) or 30^(th) new valve stateindication.

An embodiment of a blood pump control system is illustrated in FIG. 9.The system 500 includes an implantable blood pump 600 and a control unit700. The control unit may be configured for implantation or may beconfigured for controlling the pump operation from outside of the body.The blood pump and the control unit may be connected by means of cablesor wires or by means of a wireless data connection. The system may alsoinclude a transcutaneous energy transfer system to deliver energy to theblood pump too be used for rotating the rotor.

The blood pump 600 includes an inlet 610, which may be connected to theleft or right ventricle or an atrium or a pulmonary vein either directlyor via means of a canula. Blood entering the inlet 610 has a pressurep_in, which may be measured directly by a sensor located in the inlet.The blood is pumped by means of a rotor 620 driven by a brushless DCmotor, BLDC, 630 and its axial position being controlled actively by asensing coil or a plurality of sensing coils located in the stator hubs640. Permanent magnets located in the rotor and the stator hubs allowfor a passive radial control of the position of the rotor. Blood exitsthe pump through a blood outlet 650 at a pressure of p_out, which may bemeasured directly by means of a sensor located in the area of the outletof the pump. However in the present embodiment, the inlet pressure andthe outlet pressure are not measured directly. Instead the axialdistance between the rotor and the stator hub can be sensed by thesensing coils. Optionally, in combination with an axial force deliveredby a ring coil the distance can be delivered to a lookup-table, forexample, and it has been found that this distance is almost linearlyproportional with a pressure difference over the rotor. Thus, thedistance can be used as a signal representative of a pressure differencebetween the pump outlet and inlet without having to measure the pressureor pressure difference directly. In other embodiments or for other pumpsthe measured signal may be the pressure or pressure difference directlyor from another signal source than the distance.

The signal representing the distance between the stator hub and therotor is forwarded to the control unit 700 as an analogue or digitalsignal and is transmitted via cable or wirelessly.

In this embodiment, the signal 660 is received at a signal pre- andpost-processing circuit 710 of control unit 700. The signalpre-processing circuit 711 may improve the signal-to-noise ratio of thesignal, or may include a digitizing step, or may include the applicationof a frequency filter. Furthermore, the circuit may be configured todivide the signal into subsections containing data from a singleheartbeat cycle only. The circuit may be a hard-wired circuit, amicrocontroller, a programmable field array or may be simulated in amicroprocessor by means of a software or firmware stored in a memory.The circuit may be an analogue or a digital circuit.

The pre-processed signal 713 is forwarded to a microprocessor 720, whichis connected to a signal-processing circuit 730, a memory 740 and a modeoperation setting unit 750.

The signal-processing circuit 730 may be a hard-wired circuit or anemulated software circuit and routine processed by the microprocessor720. The pre-processed signal 713 is a time-series signal and signalcharacteristics are extracted from the signal and stored as a signalcharacteristics vector for the heartbeat cycle. In further example, inwhich the signal includes more than one heartbeat cycle the extractedsignal characteristics may also be stored in a matrix, a column or rowfor each heartbeat cycle. The extracted vector is processed by aclassifying circuit and reduced to a valve state indication for eachvector as previously indicated. The valve state indication is then usedto construct an AVOI. Valve state indications used for constructing theAVOI may be temporarily stored in a part of the memory 740. This part ofthe memory can also be realized as a ring buffer, or any other type ofvolatile or non-volatile memory. The constructed AVOI is compared to atarget AVOI corresponding to a mode of operation set in the mode unit750. The comparison may take place in the microprocessor 720 or may beperformed by a comparator circuit. Depending on the result of thecomparison, the microprocessor generates a signal 721 indicative of adesired rotational speed of the pump. The signal may reduce, increase ormaintain the current rotational speed. The signal 721 is postprocessed,if necessary, and forwarded by transmitter 712 of the pre- andpost-processing circuit 710 to motor 630. The motor speed is alteredaccording to the signal.

In further embodiments, the AVOI can be stored in regular intervals andtransmitted to an external programmer. Based on the AVOIs, theprogrammer can change the mode of operation from one mode to another orcan change the target AVOI range set for a specific mode or can uploadnew modes of operation.

A schematic representation of a longitudinal section through a bloodpump 1 of the type suggested here is represented schematically in FIG.10b . The blood pump 1001 comprises a hollow body 1002 (represented as acontinuous thick line), in which an impeller 1003 with a blading 1004 isprovided. Moreover, the hollow body 1002 comprises an inlet 1005 for theflow of blood in an inflow direction which is parallel to a rotationaxis R (shown dashed), and an outlet 1006 for the outflow of blood in anoutflow direction which runs perpendicular to the section plane.Accordingly, in this embodiment example, the outlet is arranged offsetat a right angle relative to the rotation axis R, for producing anoutflow angle α of α=90°, which is different from zero, between theinflow direction and the outflow direction. However, the angle α mayalso differ from 90°.

The outlet 1006 of the hollow body 1002 is arranged between anupstream-side 1009 of the impeller 1003, said upstream-side facing theinlet, and a downstream-side 1010 of the impeller 1003, saiddownstream-side being away from the inlet. An inner radius of the hollowbody 1002 serves for forming a discharge channel 1011 which runstangentially around to the impeller 1003 and runs out into the outlet1006, for a discharge of the blood out of the hollow body 1002, saiddischarge running essentially tangentially to the impeller 1003.

Moreover, two support rings 1007 are connected to the impeller 1003, forthe formation of two annular gaps 1008 between the support rings 1007and an inner wall of the hollow body 1002.

A peripheral surface 1012 of the impeller 1003, which carries theblading 1004, is formed in a cylinder-shaped manner, but may just aswell be designed in a truncated-cone-shaped or cone-shaped manner. Theaxial dimension (length) L of the impeller is selected larger than adiameter D of the impeller on the downstream-side of the impeller. Theblading of the impeller is characterised by a pitch which increasestowards the outlet 1006. In this manner one permits an axial propulsionup to the discharge channel 1011, which is particularly gentle to theblood. The blading of the impeller 1004 extends axially completely (inother embodiments partly or not at all) into the discharge channel 1011and the outflow 1006.

An inlet guide vane 1014 which is provided with a blading 1014′, isprovided in the direct vicinity of the upstream-side 1009 of theimpeller 1003.

The blood pump further comprises a partly actively stabilised bearingdevice which contains an actively stabilised, magnetic axial bearing aswell as a passive, magnetic radial bearing. The magnetic bearing devicefirstly comprises two permanent magnets 1015, 1015′ which are arrangedin the impeller at the upstream-side and at the downstream-side.Furthermore, two further permanent magnet bearings 1016, 1016′ which arepoled opposite to these (attracting) and which are integrated into theinlet guide vane 1014 and the backing plate 1013, respectively, servethe formation of the passive, magnetic radial bearing, which ensuresthat the impeller 1003 is held in a radial desired position between theinlet guide vane 1014 and the backing plate 1013. Moreover, for theactively stabilised magnetic axial bearing, two ring coils 1017, 1017′are arranged outside the hollow body 1002, in front of and behind theimpeller 1003, such that they are peripheral around the hollow body 1002in an annular manner for producing an axial magnetic flux. Moreover, themagnetic bearing device comprises a sensor system which comprisesdistance sensors 1018, 1018′ integrated into the inlet guide vane 1014and/or the backing plate 1013 as well as into the impeller 1003, formeasuring the gap widths between the impeller 1003 and the inlet guidevane 1014 or the backing plate 1013, as well as a closed-loop controlunit (not shown here) which is connected to the distance sensors 1018,1018′ and the ring magnets, said closed-loop control unit setting themagnet flux produced by the ring magnets, according to the measuredaxial position of the impeller, for correcting a possible deviation ofthe impeller from an axial desired position.

Finally, a motor winding 1019 running around the hollow body and a motormagnet 1020 integrated into the impeller are provided, said motor magnetbeing magnetised in an alternating radial manner, for driving theimpeller 1002.

In FIG. 10b , a schematic representation of a longitudinal sectionthrough a blood pump 1001 of the type suggested here is shown, whichdiffers from the blood pump described by way of FIG. 10a in that acentral, cylindrical rod 1016 extends from a downstream-side 1027 of thepump 1001 axially into the hollow body 1002 towards the impeller 1003.In said rod 1026, one of the distance sensors 1018′ is integrated formeasuring the gap width between the impeller 1003 and the rod 1026 aswell as one of the permanent magnet bearings 1016′ being a part of thepassive, magnetic radial bearing. Furthermore, the ring coil 1017′ ofthe actively stabilized axial bearing now is positioned axially beforethe outlet 1006 and runs around the hollow body 1002, while in theembodiment shown in FIG. 10a , the respective ring coil 1017′ is locatedbehind the hollow body 1002 (with respect to the axial pump direction)and consequently does not run around the hollow body 1002.

Both pumps shown in FIGS. 10a and 10b may incorporate any of the methodsor systems described in this application. Further details of the pumpscan be found in applications PCT/EP2011/002384, U.S. application Ser.No. 13/505,368 and PCT/EP2012/002009, which are incorporated herein byreference.

The invention claimed is:
 1. A method for generating a signal indicativeof a valve state, the method comprising: receiving a time-series signalrepresenting a pressure difference between a first blood pressure and asecond blood pressure over at least one heartbeat cycle; deriving atleast one signal characteristic from the time-series signal, wherein thesignal characteristic includes a relationship between, or a valuederived from, at least two different data points of the time-seriessignal; classifying the valve state of a heart valve during the at leastone heartbeat cycle based on the at least one signal characteristic,wherein the time-series signal over the at least one heartbeat cycle isseparated into a plurality of separated data sets, each of the separateddata sets comprising data from only one corresponding heartbeat cycle,and wherein the valve state is classified for at least two of theseparated data sets; generating the signal indicative of the valve statebased on the classification; and controlling a speed of a blood pumpbased on the signal indicative of the valve state.
 2. The method ofclaim 1, wherein the at least one derived signal characteristic is basedon a waveform of the time-series signal.
 3. The method of claim 1,wherein the at least one signal characteristic includes one of thefollowing: a difference between a minimal and a maximal signal valueduring a heartbeat cycle; an extremal value of a derivative of thesignal between a minimal and a maximal signal value during a heartbeatcycle; a quotient of a difference between a minimal and a maximal signalvalue during a heartbeat cycle and a maximal signal value within apredetermined number of previous heartbeat cycles; a difference betweenan end value defined by an intersection value of a tangent line throughan extremal point and a tangent line through a minimal signal value andthe minimal signal value, DUR; an area bordered by the tangent lines,AREA; and an angle between the tangent line through an extremal pointand a line connecting the minimal signal value and a value of thetime-series signal corresponding to the end value (α).
 4. The method ofclaim 1, wherein the valve state is classified by a trained classifier.5. The method of claim 1, wherein two or more signal characteristics arederived.
 6. The method of claim 1, wherein two or more signalcharacteristic are derived and classifying the valve state based on thetwo or more signal characteristics.
 7. The method of claim 1, whereinthe first blood pressure is representative of a ventricular pressure andthe second blood pressure is representative of an aortic pressure. 8.The method of claim 1, wherein the heart valve is any of: an aorticvalve, a pulmonary valve, or a mitral valve.
 9. A blood pump controlsystem including: a signal characterizing circuit configured to deriveat least one signal characteristic from a time-series signal indicativeof a pressure difference between a first blood pressure and a secondblood pressure over at least one heartbeat cycle, wherein the signalcharacteristic includes a relationship between, or a value derived from,at least two different data points of the time-series signal; and aclassifying circuit configured to determine a classification of a valvestate of a heart valve for at least parts of the time-series signalduring the at least one heartbeat cycle based on the at least one signalcharacteristic, wherein the classifying circuit is configured toseparate the time-series signal over the at least one heartbeat cycleinto separated data sets, wherein each separated data set including datafor only one corresponding heartbeat cycle, and wherein theclassification of the valve state includes a correspondingclassification for at least two of the separated data sets; and acontroller operably connectable to a blood pump and configured to adjusta speed of the blood pump based on the classification of the valvestate.
 10. The system of claim 9, wherein the classifying circuit isfurther configured to generate a signal indicative of the valve state ofthe heart valve based on the classification.
 11. The system of claim 9,wherein the controller is configured to receive a valve state index(VSI) signal and adjust a speed of a movable element of the blood pumpbased on the VSI signal, wherein the VSI signal is based on theclassification.
 12. A method comprising: deriving at least one signalcharacteristic from time-series data of a signal over at least oneheartbeat cycle, the signal representing a pressure difference between afirst pressure and a second pressure over the at least one heartbeatcycle, wherein the at least one signal characteristic includes arelationship between, or a value derived from, at least two differentdata points of the time-series data; classifying a valve state of aheart valve during the at least one heartbeat cycle based on the signalcharacteristic, wherein the time-series data over the at least oneheartbeat cycle is separated into a plurality of separated data sets,each of the separated data sets including data for only onecorresponding heartbeat cycle, and wherein the valve state is classifiedfor at least two of the separated data sets; and controlling a heartpump based on the classification of the valve state.
 13. The method ofclaim 12 wherein the controlling the heart pump comprises adjusting aspeed of the heart pump based on the classification of the valve state.